Anatomies of Sexism

Month: Aug 2017

In the last post we saw that in order for a type to be considered real – that is, a natural object – a group of individuals must have more in common with one another than with any individual excluded from that group. It’s already quite clear that by this definition, Simon Baron-Cohen’s “brain types” are not really types at all. Look at the graph again, and you’ll see that many individuals actually have more in common (more similar scores) with another individual on the other side of a boundary line than with most individuals within their own colour zone. .

Those stripes of colour don’t even represent distinct types of score, let alone distinct types of brain. They are nothing more than stripes of colour painted across an arrangement of individuals’ results on two self-reporting questionnaires.1

And that isn’t all:

Even if Baron-Cohen’s vague and arbitrary groupings did tick all the boxes to be considered “types” in the taxonomic sense, typological thinking actually went out of fashion ages ago as evolutionary biology gained currency. There are those, like Wilkins and Ebach (quoted in my last post) who argue that typology does have a place in biology – in descriptions, at least – but as they themselves point out, typology is now generally “regarded as a regressive and pre-evolutionary approach to the data and biology.”2 The question, then, is whether types exist at all.

Let’s go back to the beginning.

The Linnaean taxonomy is so much a part of our tradition that most of us will have grown up feeling that the grouping and naming of living things by genus and species – as in homo sapiens and my personal favourite, rattus rattus – reflect a tangible genetic reality that exists outside of human thought.

But “species” and “genus” were concepts that Carl Linnaeus inherited from Plato and Aristotle. It was in an ancient tradition, and in perfect freedom from the framework of evolutionary theory and genetics, that in 1735 Linnaeus constructed the system of classification we still use today. Yes, it has evolved with evolutionary theory; indeed, Linnaeus modified it a number of times himself. Nevertheless, its whole aim, as well as its structure and concepts, is rooted in a tradition of essentialism.

Very, very briefly: Plato, like many philosophers before him, observed that the world around him was in constant flux: unstable and always changing. He proposed that behind this wobbly material world there was another, more stable reality: the world of ideas. Material world objects like Plato himself, like a particular horse or a particular house, were in fact only imperfect shadows of the perfect and unchanging ideas or forms, man, horse and house. These ideal forms were called species. Plato is of the species man. Species were grouped into genera (plural of genus). Man and horse are both of the genus animal; house may be said to be of the genus building.

Next came Aristotle, who termed the defining idea or form of a thing its τὸ τί ἦν εἶναι, conventionally rendered in English as essence; the most common literal translation is “what-it-is-to-be.” There are other translations, but they generally communicate this sense of design: of what something is supposed to be.

And there you have the basis of essentialism. It’s a doctrine that has enjoyed profound – perhaps unparalleled – influence. Medieval Christian churchmen thought in these terms: God had created an natural order of unchanging forms, of which the material forms were imperfect representations. Early naturalists like Linnaeus were working within this tradition of Christian and essentialist thought. The members of a species shared a unique and unchanging essence, and the essence defined the species.

Trouble was, it actually proved rather tricky to locate the darned thing. To find a trait that is shared by every single member of every generation of a species for its entire life on the planet, and not shared by any member of any other species, is nigh on impossible.

R.I.P. Essentialism; enter Darwinism.

In theory, that is. In practice, the death of essentialism is about as much a natural object as were those elusive essences themselves.

1The paper does not specify how boundaries were decided. They may represent standard deviations from the mean, but even if this were the case this signifies no more than your distance from the mean score ratio…

2Wilkins and Ebach, The Nature of Classification: Relationships and Kinds in the Natural Sciences.

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Now, it’s difficult to believe, but those questionable questionnaires, the EQ and the SQ, are in fact the only tools that Simon Baron-Cohen uses in the diagnosis of brain sex. We’ve already identified a number of flaws that undermine their reliability as tools for diagnosing anything other than your own opinion of yourself, or perhaps how middle class you are,1 but let’s overlook this for a moment and consider the statistics they produce.

(NB. You’re supposed to take both and compare your scores. If you score higher on the SQ, you have a “systemising” or “male” brain, represented as S > E (S is greater than E); if you score higher on the EQ, you have an “empathising” or “female” brain, represented as S < E (S is smaller than E). If you score equally on both, you have a “balanced” brain, represented as S ≈ E.)

The following table is taken from a 2005 paper listed on Baron-Cohen’s University of Cambridge page as one of his “key publications,” notable as his only paper ever published in the reputable journal Science.2

Now, observe that only 48.5% of women actually have any sort of “female” brain (adding the “Extreme female” and “Female” scores). Even using his own gender-stereotype detection tools, Simon Baron-Cohen finds that 51% of women do not have “the female brain.” (Remember, the female advantage in empathising narrows or disappears when the tools are less subjective.3) What, then, makes this kind of brain so very female? I rather wish that Baron-Cohen’s brand of mathematics had been applied to the EU referendum last year: the 48.11% for Remain would have been considered more representative of the people’s will than the other 51.89% and my £££ would still afford me a decent number of croissants at family reunions in France.

The SQ does net a slightly higher proportion of men, at 59.6%, but that isn’t exactly an overwhelming majority either, even though the SQ is more blatantly gendered male. Do these numbers really merit classification into “neurophysiological” types?

Have a look at this figure, from the same page:

Even overlooking the fact that the numbers on the x and y axes here refer to nothing more than people’s scores on those subjective and stereotyped self-report questionnaires, this graph actually shows a good deal of overlap between the red diamonds representing women and the blue triangles representing men (I won’t be discussing the green squares representing people diagnosed with Autism Spectrum disorders). But the diagonal stripes of colour are supposed to show that, in fact, those clustered questionnaire-scores are in fact produced by five distinct “brain types”.

Now ask yourself who decided where the “boundaries for the different brain types” should be drawn, and how this was decided. Do those lines really mean anything?

Consider the three red diamonds clustered where the Systemizing 30 line crosses the Empathizing 40 line, at the boundary of the “Balanced” (white) and “Systemizing” (light pink) zones. Those diamonds represent three women notdiagnosed with an Autism Spectrum Disorder. One is in the white zone (we’ll call it Diamond A), and two (Diamonds B and C, from left to right) lie just inside the pink zone (on top of two blue triangles, which represent two men who got the same scores as these women). Diamond A and Diamond B have the same SQ score, but are two points apart on the EQ axis and happen to fall in different zones; Diamonds B and C have different EQ and SQ scores, but both fall within the pink ‘Systemising’ zone. According to Baron-Cohen Diamonds B and C are of one type, while Diamond A is in another category entirely. But is this really convincing? Do we really believe that Diamond A represents a woman with a different type of “neurophysiology?”

What is a type anyway?

Of course we all think we know what a “type” is: it’s a word we all use. But Baron-Cohen claims to be doing “science” here, and so we must hold him to scientific standards.

In the language of the natural sciences, a “type” signifies “a group or division of animals, etc., having a common form or structure” (OED 8.a.). Baron-Cohen is tapping in, here, to the vocabulary of taxonomy (the classification of organisms in the biological sciences of bottany and zoology); or, to be precise, the vocabulary of Linnaean Taxonomy.

Most readers will be familiar with this system of taxonomy (which is the dominant system today, although it has adapted over the years), whether they realise it or not: the organisation of animals and plants by species, genus, family, order, class, phylum and kingdom.

Now, the Linnaean system was originally a typological taxonomy: Carl Linnaeus grouped organisms by observable type. Modern taxonomists have moved away from typology, but I’ll deal with that in my next post. For now, let’s just look at what does constitute a type if you’re into that sort of thing. According to a recent book supporting typological classification, “types are crucial in most natural classification because they are the phenomena around which classifications are made.”4 That is to say, phenomena (e.g. animals or plants) are observed, patterns (similarities in structure) are noted, individuals sharing characteristics are grouped into “types,” and then classifications are made based on these types.

But to be considered a type in its own right, an individual or group of individuals must be sufficiently different from the others already known to us:

we recognize the specimen as a “different type” only because we already have prior knowledge of things that are in relationship to it and identify that it does not fit neatly into the patterns they generate. Hence, there is a pattern, but it is a pattern of exclusion: the new taxon is formed from the joint assumption that the specimen must reside in a taxon, and that it does not reside in existing related taxa. (ibid.)

And for an observed type to become a classification, the quality and degree of difference has to be well-established. In The Classification of the Sciences, Herbert Spencer, one of the first evolutionary biologists and contemporary of Charles Darwin, offers this simple and elegant definition:

A true classification includes in each class, those objects which have more characteristics in common with one another, than any of them have in common with any objects exluded from the class.

Now, are we entirely persuaded that the women behind Diamonds B and C must have more in common with one another than with the woman behind Diamond A? Even though A and B actually have an SQ score in common?

More on types tomorrow. For now, let me leave you with a link to another blog post, written today by a friend of mine (it’s a great read, and not just because I have a cameo role in it). She studied maths at Cambridge and afterwards went into computer programming (sounds systemisey, doesn’t it?), while I studied English and have more or less been reading fiction full time since I graduated (empathisey?) – and yet her blog is far more aesthetically pleasing and person- or emotions-related than this one, which is turning out to be more systematic than anything I ever thought I’d write. Perhaps we accidentally swapped brains one day when we were out jogging together.

She can still code like nobody’s business, though, while I can barely handle a ready-made WordPress domain…

1We have seen that the questions themselves are not demonstrably linked to “neurophysiology” so much as to contemporary, occidental, middle-class gender stereotypes. It is not at all clear that Baron-Cohen’s chosen examples of “systemising” really do demonstrate that function (is football really more systemising than knitting?). We have also seen that an individual’s score may be affected by the way they see themselves and would like to be seen – as more systemising or as more empathising – and that it is likely to fluctuate throughout one’s lifetime.

4Wilkins and Ebach, The Nature of Classification: Relationships and Kinds in the Natural Sciences (Palgrave Macmillan, 2014). Quotations are taken from the Google Books preview that does not give page numbers.

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Let’s look at some more examples from the Systemising Quotient that Simon Baron-Cohen uses to ascertain if you have the “male brain:”

“4. I prefer to read non-fiction than fiction.”

In order to be able to score points towards systemising you have not only to be literate (and outside the affluent classes of the West, illiteracy is common), but enough of a reader to have a genre preference. And then, what about computer programmers who like to read fiction in their free time? Don’t they have systemising brains?

“7. If there was a problem with the electrical wiring in my home, Iʼd be able to fix it myself.”

As well as highly gendered, this question can only test for systemising in people with homes with wiring. A large proportion of the global population live without electricity in their homes. And what about the homeless? Apparently they can’t systemise. Or, for that matter, what about people who have only ever rented? You probably get more involved with the wiring if you’re a homeowner, or grew up with parents who were homeowners…

“11. I rarely read articles or Web pages about new technology.”

You have to disagree with this one to get points, which means that in order to qualify for the systemising brain you have to have internet access – which, again, a large proportion of the global population do not.

“18. I find it difficult to understand instruction manuals for putting appliances together.”

You have to have buying power as well be literate in order to have a systemising brain.

“19. When I look at an animal, I like to know the precise species it belongs to.”

You have to have learned about Linnaean Taxonomy in order to score points.

“24. I find it difficult to read and understand maps.”

You are more likely to have been born with the male brain if you later became a scout or if your school offered the Duke of Edinburgh Awards as an extracuricular activity.

“29. When I read the newspaper, I am drawn to tables of information, such as football scores or stock market indices.”

Again, you must be literate, but you must also be interested in football – which, as I suggested in my last post, may have very little to do with systemising – because I rather doubt that many people are interested in these tables unless they are interested in the information communicated by them.So it would seem that you are more likely to have been born with the male brain if you will one day have enough money to buy stocks.

“30. When I learn a language, I become intrigued by its grammatical rules.”

You have to have learned at least one foreign language in order to have the systemising brain.Not only that, but you must have studied it formally so as to gain exposure to its grammatical rules.In short, you need to have gone to a good school to have the male brain.

“32. I do not tend to watch science documentaries on television or read articles about science and nature.”

I haven’t been able to find a study on this, but I suspect that country, age, socio-economic and educational background all have something to do with how likely you are to watch science documentaries – let alone own a television or computer to watch with.By way of anecodotal evidence I would point out that lately I have been watching and reading more documentaries and articles and books about science than I used to.Health scare: has my brain changed type this year?

And again, you should also be literate to have the male brain. But until someone produces the data to prove otherwise, I remain unconvinced that all mathematicians, knitters, tailors and computer programmers are thrilled by science documentaries.

“34. I find it easy to grasp exactly how odds work in betting.”

I have never tried to grasp how odds work in betting, so I’ll lose systemising points.But if now I did try to learn how odds work, and found it easy, would I suddenly change brain type?

“41. When traveling by train, I often wonder exactly how the rail networks are coordinated.”

You have to live in a country with a rail network in order to have a systemising brain.

“51. When Iʼm in a plane, I do not think about the aerodynamics.”

You have to have travelled by aeroplane to have a systemising brain.That rules out all the people without money for air travel, most of those without passports, and anyone who died before air travel became common.

“56. I do not read legal documents very carefully.”

Literacy and living a lifestyle that involves legal documents is a prerequisite for having been born with the male brain – which rules out a huge proportion of the world’s population, including most of my friends in Uganda.

A bit of brevity and levity for today’s post.Nevertheless, it should demonstrate that the Systemising Quotient is not a tool with which to accurately diagnose “brain type” across ages, cultures and socio-economic groups – not to mention across a single individual’s life span.Interests, habits and even aptitudes change over the course of a life.If empathising and systemising really do “depend on independent sets of regions in the human brain,”1 this sort of questionnaire isn’t going to locate those regions.

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Let’s go back to Baron-Cohen’s definition of systemising. In an essay entitled ‘Why So Few Women in Math and Science?’ he introduced it like this:

As systemizing is a new concept, it needs a little more definition. By a “system” I mean something that takes inputs and delivers outputs. To systemize, one uses “if–then” (correlation) rules. The brain focuses on a detail or parameter of the system and observes how this varies—that is, it treats a feature of a particular object or event as a variable. Alternatively, a person actively or systematically manipulates a given variable. One notes the effect(s) of performing an operation on one single input in terms of its effects elsewhere in the system (the output). The key data structure used in systemizing is [input–operation–output]. If I do x, a changes to b. If z occurs, p changes to q. Systemizing therefore requires an exact eye for detail.1

Forgive me for dumping this rather dense paragraph, but it’s important. Read it carefully. And ask yourself where such systemising is to be found. Where have you performed or observed someone performing this kind of systemising?

Now this is what Baron-Cohen has to say:

“The relevant domains to explore for evidence of systemizing include any fields that are, in principle, rule-governed. Thus, chess and football are good examples of systems.” (12)

Chess and football happen to be predominantly masculine pursuits in this world of ours. Remember the SQ statements that were similarly gendered male. But what about knitting? I’d call that a system that takes and delivers outputs.2 Why has that never been included on the SQ?

Just a few lines before giving football as an example, Baron-Cohen told us that “Systemizing is of almost no use for predicting moment-to-moment changes in a person’s behavior, but it is our most powerful way of understanding and predicting the law-governed, inanimate universe” (12). But football isn’t law-governed and inanimate; “moment-to-moment changes in a person’s behaviour,” which he tells us cannot be predicted by systemising, are enormously significant in football. The moment-to-moment decisions of the players are unpredictable; using the same strategy (input) in football will not always generate the same result (output) because it depends a) on how effectively you execute it in a given situation, and b) on how the opposition respond. Weather, and players’ healths and moods consititute variables and create further uncertainty. If football were really all that predictable we’d always know who was going to win! Actually, the same goes for chess. Your input does not always deliver the same output because it depends on the moves made by the other player.

Knitting, on the other hand, is far more “law-governed” and “inanimate”. Back to The Essential Difference, where “Systemizing is the drive to analyze, explore, and construct a system.” Actually, the more I think about it, the more knitting looks like a perfect example. “The systemizer intuitively figures out how things work, or extracts the underlying rules that govern the behavior of a system. This is done in order to understand and predict the system, or to invent a new one.” (13) Yes. To knit, one must understand the system. And one must extract the underlying rules of knitting and of patterns in order to invent a pattern of one’s own. Spatial skills (like rotation), stereotyped as masculine, are also necessary

Making clothes (out of cloth, rather than knitting), whether by hand or with a sewing machine, requires a similar set of skills; rotation must be even more important here. So why aren’t these items on the systemising quotient? If they were, more women would score more points, while men might lose a few; suddenly, systemising wouldn’t look quite so male-dominated.

1 In The Science on Women and Science, ed. Sommers (Washington, D.C., 2009), p.11. Hereafter page numbers will be given in the text. It’s rather important to be aware that this was a collection of essays put together to combat the idea that something ought to be done to get more women into science. (Sounds a bit like Damore’s memo, doesn’t it?) If that isn’t science with a political agenda, I don’t know what is. I’ll return to a discussion of this in another post.

2Interestingly, in a 2009 paper submitted to Tizard Learning Disability Review, Vol 14.3, he included “learning knitting patterns” as an example of “motoric systemising” in individuals on the autistic spectrum. Perhaps he included it in response to the criticisms of his gender-biased quotient, or because in this case the paper was about “implications for education” and educators/parents might not have been happy with examples that were all gendered male. But it’s significant that he includes it as “motoric systemising” and equivalent to “learning…a tennis technique” rather than classing it, for instance, under “numerical systemising.” And, even more significantly, knitting was never included on the SQ – not even the revised version reissued in the wake of criticisms.

The problem is, “The Science” doesn’t exist. There is no one science. Science is not a single laboratory in which a single group of scientists find and publish The Facts. There are many sciences, or scientific fields, and the myriad scientists working across them do not all agree – in fact, they don’t even all agree on what exactly qualifies as “science.”

It’s useful to remember that “science” used to denote just “knowledge,” or “knowledge or understanding acquired by study” (OED 2) and that in modern French it still has this broader meaning. (And it’s always in the plural in French and German.)1 What we call “the scientific method” is just one way of trying to generate knowledge; an exaggerated faith in this method alone, in “evidence,” “data,” “statistics” and nothing else, is sometimes known as scientism, a term also used to denote the improper use, or improper understanding, of science and scientific findings.2 A phrase like “the science says” is closer to scientism than science.

And even within the scientific method – by the scientific method’s own logic – no one study or finding is ever conclusive alone; indeed, multiple studies together are rarely entirely conclusive. A phrase like “scientists have shown” or “a study has shown” should be used to start up a discussion, not to close it down.

It’s also important to remember that no science can ever be entirely objective; individual scientists still less so, however much some of them like to pretend that they are. A statement like “it isn’t sexist, it’s science” sets up a false dichotomy: science can be sexist. Science can be racist. Science is not conducted in a vacuum, safe from the influence of politics. As Dr Anne Fausto-Sterling puts it, “there is no such thing as apolitical science. Science is a human activity inseparable from the societal atmosphere of its time and place.”3

So when someone claims that “it isn’t sexist, it’s science,” or that “scientists have shown” X, Y or Z, it’s important to ask which science. Let’s have a look at Damore’s.

He seems to have lifted his ideas from Wikipedia (rather than from original sources like books and journals, which isn’t very convincing if you’re trying to be “scientific.”; have a look at the Wikipedia page on “neuroticism” and you will notice distinct similarities in phrasing – if it hasn’t been edited out of recognition by the time you check), but one major influence is Simon Baron-Cohen, author of the “empathizing vs. systemizing” (or “empathizing-systemizing”) theory that Damore cites (without acknowledgment).

Baron-Cohen is a professor of psychology at Cambridge University, where I obtained my degree. Where you find the phrases “empathising vs. systemising,”“prenatal testosterone,” “male brain” and “female brain,” there’s a good chance that Baron-Cohen’s nearby.4 But although he’s popular, his work has also attracted criticisms in the scientific community. We’ll come to those. First, let’s have a little look at his theories, his methods and his findings:

The following quotations are taken from his popular science book (by “popular science” I mean it wasn’t peer-reviewed and so didn’t have to be held to a certain academic standard) called The Essential Difference: Male and Female Brains and the Truth about Autism (2003), but he first began publishing on this theory in 19975 and identical phrasings are found in a number of his works. He defines “three main brain types”:6

“the female brain – empathizing” (p.11),

“the male brain – systemizing” (p.13),

“the balanced brain,” where “systemizing and empathizing are both equally strong” (p.17).

Supposedly, “the female brain is predominantly hard-wired for empathy” while “the male brain is predominantly hard-wired for understanding and building systems” (p.11). He claims that “ultimately, systemizing and empathizing depend on independent sets of regions in the human brain” and that “they are not mystical processes but are grounded in our neurophysiology” (p.16).

These are bold claims. But how does he actually propose to measure your “neurophysiology” and diagnose your “brain type”? With questionnaires, mostly.

He has developed two sets of statements for which you have to choose Strongly Agree/Slightly Agree/Slightly Disagree/Strongly Disagree, and then add up your score at the end. One is called the “Empathy Quotient” (sometimes the “Empathizing Quotient”), abbreviated to the “EQ” to make it sound a bit more scientific, and another set called the “Systemizing Quotient”, or “SQ”; you can find them both online but I’ll be referring to the versions included as appendices in The Essential Difference.

The EQ includes statements like 22. I find it easy to put myself in somebody elseʼs shoes, 42. I get upset if I see people suffering on news programs, and 43. Friends usually talk to me about their problems as they say that I am very understanding. It’s quite plain that these questions are asking you to report how nice you think you are. Does this seem like a robustly empirical and objective way of measuring a cognitive function governed by a particular set of regions in the brain?

Not all psychologists place so much faith in self-reporting questionnaires. Cordelia Fine, who is Professor of History and Philosophy of Science at the University of Melbourne, puts it this way: “to find, as Baron-Cohen does, that women score relatively higher on the EQ is not terribly compelling evidence that they are, in fact, more empathic.”7 Fine gathers together a number of criticisms of such methods, including “an important review of gender differences in affective empathy” which reported that “no gender difference was found for studies using unobtrusive physiological or facial/gestural measures as an index of empathy.) In other words, women and men may differ not so much in actual empathy but in ‘how empathetic they would like to appear to others (and, perhaps, to themselves)’”.8

As for the SQ, a number of critics have remarked upon the fact that the tendencies and interests supposed to indicate that your brain is “hard-wired for understanding and building systems” are very obviously gendered male: 5. If I were buying a car, I would want to obtain specific information about its engine capacity, 7. If there was a problem with the electrical wiring in my home, Iʼd be able to fix it myself, 13. I am fascinated by how machines work, and 25. If I had a collection (e.g., CDs, coins, stamps), it would be highly organized. Answering “Strongly Agree” for any of these fetches two points apiece.

Fine cites philosopher Neil Levy pointing out that many of the questions in the EQ and SQ are actually “testing for the gender of the subject, by asking whether the subject is interested in activities which tend to be disproportionately associated with males or with females (cars, electrical wiring, computers and other machines, sports and stock markets, on the one hand, and friendships and relationships, on the other)” (562).

I’ll be back tomorrow with more on the empathising-systemising theory; for now, my female brain (tired out with all this unnatural systemising of evidence and argument) needs its beauty sleep.

1One definition of “science” still current today is “the kind of organized knowledge or intellectual activity of which the various branches of learning are examples,” (OED 5.a.) which used to be used interchangeably with “philosophy.” The most commonly understood definitions in English today didn’t gain currency until the nineteenth century: “A branch of study that deals with a connected body of demonstrated truths or with observed facts systematically classified and more or less comprehended by general laws, and incorporating trustworthy methods (now esp. those involving the scientific method and which incorporate falsifiable hypotheses) for the discovery of new truth in its own domain” (OED 4.b.), and “The intellectual and practical activity encompassing those branches of study that relate to the phenomena of the physical universe and their laws, sometimes with implied exclusion of pure mathematics” (OED 5.b., a narrower definition than 4.b., otherwise known as “natural science”). The only case in which one should use the phrase “the science” is as a synonym of “the data;” that is, locally and specifically,, within the context of a single study or specified studies.

2OED 2: Chiefly depreciative. The belief that only knowledge obtained from scientific research is valid, and that notions or beliefs deriving from other sources, such as religion, should be discounted; extreme or excessive faith in science or scientists. Also: the view that the methodology used in the natural and physical sciences can be applied to other disciplines, such as philosophy and the social sciences, <http://www.oed.com/view/Entry/172696?redirectedFrom=scientism#eid> [accessed 13 August 2017]; ‘The Basics of Philosophy,’ <http://www.philosophybasics.com/branch_scientism.html> [accessed 13 August 2017].

4A note on spellings: in many of Baron-Cohen’s publications, although he is British, the American English spelling is used (e.g. “systemizing” rather than “systemising”. When quoting I use the spelling used by the author; when writing in my own words, I will use the British English spelling.

5Baron-Cohen and Hammer, ‘Is autism an extreme form of the “male brain”?’ Advances in Infancy Research 11 (1997), 193-217.

6Baron-Cohen, The Essential Difference: Male and Female Brains and the Truth about Autism (New York, 2003), p.16. Hereafter page numbers will be given in brackets in the text.

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Here is an extract from Damore’s memo, with my commentary. His words in blue, mine in black:

Possible non-bias causes of the gender gap in tech [3]

At Google, we’re regularly told that implicit (unconscious) and explicit biases are holding women back in tech and leadership. Of course, men and women experience bias, tech, and the workplace differently and we should be cognizant of this, but it’s far from the whole story. On average, men and women biologically differ in many ways. [True.] These differences [but notice how vague he is] aren’t just socially constructed because:

They often have clear biological causes [it seems a bit obvious to say that reproductive organs have “biological causes”; this is where it becomes apparent that he is not in fact talking about our bodies but perhaps our minds and behaviour] and links to prenatal testosterone [Well, “differences” like testicles ALWAYS have “links” to prenatal testosterone, in that they begin to make it, from about 8 weeks into gestation – the gestation of the male foetus, that is.

But it’s perfectly clear by now that Damore isn’t talking about bodily differences. In fact, the phrase “prenatal testosterone” is generally a pretty good indicator that someone (probably Simon Baron-Cohen: we’ll come back to him) is about to start talking about the ways in which men and women think/behave differently. Google it, and most of the top results are about “gender-related behaviour”: high prenatal testosterone makes men more likely to take risks, abuse substances and be psychopaths in adult life (yes, I was right – a Simon Baron-Cohen reference!);1 high prenatal testosterone makes men more courteous to women but not to other men.2 Yes, there are a number of studies that have reported links between prenatal and testosterone and gendered behaviour. They tend to be published by psychologists, as is the case with the above-cited studies that came up when I googled ‘prenatal testosterone’. I’m going to be talking about such studies a lot in the course of this series, but for now let me just assure you that their findings are not universally accepted, and neither are the supposed differences “universal across cultures”, as Damore rather brashly suggests.]

Biological males that were castrated at birth and raised as females often still identify and act like males [Vague again, and innaccurate too. What he’s tapping into here is the discourse of a particular nature/nurture debate that raged for years between Milton Diamond and John Money; the case study in question (known as the John/Joan or Joan/John case) was of an individual whose penis was destroyed in a botched circumcision, who had sex reassignment surgery more than a year after birth, and who later reassumed a male identity under the name David Reimer. Still later he committed suicide. Milton Diamond and many others following him have concluded that gender identity is fixed before birth, but this is not unanimously agreed upon within the scientific community. Research goes on. Again, I will return to more such studies; for now, I’ll just throw in a complication or three:

First, there are a great many reasons that a child who has undegone sex reassignment may not be well-adjusted: surgery is traumatic, as may be the frequent examinations by medical professionals and the sessions with psychiatrists. And just because parents have decided (sometimes under duress from medical professionals) they are going to raise their child as a girl, it does not follow that they will treat that child in the way that the majority of girls are treated.

Second, in order to decide whether sex reassignment to female has been successful, we must first agree on what it means for children “to identify and act like males” or females – and that, apparently, isn’t easy. For many, including Milton Diamond in the 1960s, if the reassigned-female individual later had female sexual partners, or even just fantasised about other females, the reassignment had not been successful. But is attraction to females inherently male? If so, a great many women must really be men, and even more individuals must have the wonderful ability to be sometimes male, sometimes female – like fish! These days, sexual orientation is less likely to be considered a good marker of gender identity, but we still rely upon case studies that were assessed by medical professionals who used this standard.

Third, the high profile studies have tended to focus on genetic and gonadal males reassigned female. Considering that we live in a gender hierarchy (no, come on, there’s no denying it: quite apart from the pay gap and the fact that men are still more likely to be leaders, “tomboy”, though sometimes useddisapprovingly, has never been as insulting as “sissy”), a child’s desire to assume a male rather than a female identity cannot entirely be ascribed to prenatal testosterone.]

The underlying traits are highly heritable [Vague again. Sounds a bit like he’s suggesting that sex is heritable – which in a sense is true, given that we get our X and Y chromosomes from our parents – but I don’t think that’s what he means. But if, let’s imagine, he’s referring to the “traits” that make one a good Google engineer, then the jury is still out on whether these are passed from parent to child in the genes or in the time the child spent together.]

They’re exactly what we would predict from an evolutionary psychology perspective [I love this point; it’s just so explicit about its own assumptions. The fact that one would predict something from an evolutionary psychology perspective doesn’t mean it must be true, a) because it’s just that, one perspective among many others; b) because it’s exactly this kind of “prediction” – founded on a previously held belief – that causes someone to feel certain that what they see before them confirms their suspicion. Someone who believes that they already know the answer can easily, and perhaps unconsciously, lower their standards of scientific rigour and accept “findings” that are not really empirically proven. All researchers are prone to this pitfall; it’s known as confirmation bias, and good research must take steps both to reduce and to acknowledge it.]

Note, I’m not saying that all men differ from women in the following ways or that these differences are “just.” I’m simply stating that the distribution of preferences and abilities of men and women differ in part due to biological causes and that these differences may explain why we don’t see equal representation of women in tech and leadership. Many of these differences are small and there’s significant overlap between men and women, so you can’t say anything about an individual given these population level distributions. [This is very much the same structure of defence as used by Simon Baron-Cohen: “When I talk about sex differences in the mind, I am dealing only with statistical averages. And if there is one point to get across at the outset, it is this: looking for sex differences is not the same as stereotyping. The search for sex differences enables us to discover how social and biological influences act on the two sexes in different ways, but it does not tell us about individuals.”3 But such disclaimers are mere lip service paid to political correctness, using the language of science and science to veil stereoptypes in respectability. Later, when we look at the methods Baron-Cohen uses to arrive at his “statistical averages,” this will become clear.]

Personality differences

Women, on average, have more:

Openness directed towards feelings and aesthetics rather than ideas. Women generally also have a stronger interest in people rather than things, relative to men (also interpreted as empathizing vs. systemizing).

[This is a direct, though unacknowledged, reference to Baron-Cohen’s empathizing-systemizing theory that “the female brain is predominantly hard-wired for empathy” while “the male brain is predominantly hard-wired for understanding and building systems.”4 Damore drops in this reference as though it were indisputable fact, but that is very far from being the case. Baron-Cohen being my nemesis I will return to an assessment of his theories at some length…]

These two differences in part explain why women relatively prefer jobs in social or artistic areas. More men may like coding because it requires systemizing and even within SWEs, comparatively more women work on front end, which deals with both people and aesthetics. [Still Baron-Cohen. And this suggestion that women are underrepresented in STEM fields (science, technology, engineering and maths) because they just don’t like all those unpleasantly “thing”-centred jobs on account of their brains being hard-wired for childcare, is nothing more than the latest way of saying that women are constitutionally unsuited to masculine pursuits and would become hysterical if they were allowed to do them.]

Extraversion expressed as gregariousness rather than assertiveness. Also, higher agreeableness. [Another way of saying that women are chatters, men are leaders. The unacknowledged source here is Wikipedia; visit the page on ‘neuroticism’ and you may see the affinities with Damore’s piece, although an editing war rages over the content so I can’t be sure the phrases lifted by Damore will still be there by the time you follow my suggestion… In any case, Wikipedia is hardly the bastion of empiricism. I will be returning to these ideas in the course of the series.]

This leads to women generally having a harder time negotiating salary, asking for raises, speaking up, and leading. Note that these are just average differences and there’s overlap between men and women, but this is seen solely as a women’s issue. This leads to exclusory programs like Stretch and swaths of men without support. [I think it’s true that women may have a harder time negotiating salaries etc etc., but there is as yet no conclusive evidence that ability to negotiate a salary is determined by prenatal testosterone. I’ll come back to this.]

Neuroticism (higher anxiety, lower stress tolerance).This may contribute to the higher levels of anxiety women report on Googlegeist and to the lower number of women in high stress jobs. [See “Extraversion” point above.]

Note that contrary to what a social constructionist would argue, research suggests [note how he sneakily constructs a dichotomy between “social constructionists” and the implied “researchers” – as though researchers cannot be social constructionists] that “greater nation-level gender equality leads to psychological dissimilarity in men’s and women’s personality traits.” Because as “society becomes more prosperous and more egalitarian, innate dispositional differences between men and women have more space to develop and the gap that exists between men and women in their personality becomes wider.” [An unacknowledged quotation: how very academically rigorous. I traced it down to a 2008 paper published by a group of psychologists in the Journal of Personality and Social Psychology5(but I suspect Damore actually lifted the quotation from a blog post entitled ‘Time to stop first world “gender gap” hysteria: Men and women make different vocational choices’, which has more in common with his memo than the original study does). The lead author of the study, David P. Schmitt, has responded this week, speaking to Wired (‘Even the guy behind the research thinks that Googler is wrong’; here Professor Gina Rippon also highlights for Wired readers the ways in which Damore has misunderstood or misrepresented research) and publishing a blog post rejecting Damore’s position.

He points out that the sex differences found by studies like his are not large enough to account for the employment and pay gaps between the sexes and “ unlikely to be all that relevant to the Google workplace.”6 While he thinks that sex differences in personality may “play some role”, he also argues that “there have been (and likely will continue to be) many socio-structural barriers to women working in technological jobs. These include culturally-embedded gender stereotypes, biased socialization practices, in some cultures explicit employment discrimination, and a certain degree of masculinization of technological workplaces. Within this sea of gender bias, should Google use various practices (affirmative action is not just one thing) to especially encourage capable women of joining (and enjoying) the Google workplace? I vote yes.”

So, while Schmitt does think that certain sex-differences are “culturally universal and biologically-linked,” and that some of these may constitute some of the reason for gender employment and pay gaps, and that we should be able to discuss all this openly, even he does not support Damore’s position. Meanwhile, others in the scientific community do not find that sex differences in personality are so great, nor agree that they are culturally universal or innate. Keep in mind thatSchmitt takes an evolutionary psychological approach, which other members of the scientific community reject or criticise. (Just for instance, Dorothy Einon and Cordelia Fine have criticised the mathematics and logic behind the evolutionary psychological assumption that promiscuos men would have fathered more children and so passed on their genes.7 Their arguments are both brilliant and amusing, and I will return to them in another post.) But back to Damore:]We need to stop assuming that gender gaps imply sexism. [Note that he poses as the radical thinker offering brand new criticisms, whereas in actual fact there have always been voices denying that gender gaps implied sexism – even when women weren’t allowed to vote. “Different but equal” was the Victorian approach to gender roles.]

Men’s higher drive for status

We always ask why we don’t see women in top leadership positions, but we never ask why we see so many men in these jobs. These positions often require long, stressful hours that may not be worth it if you want a balanced and fulfilling life.

Status is the primary metric that men are judged on[4], pushing many men into these higher paying, less satisfying jobs for the status that they entail. Note, the same forces that lead men into high pay/high stress jobs in tech and leadership cause men to take undesirable and dangerous jobs like coal mining, garbage collection, and firefighting, and suffer 93% of work-related deaths. [I’m inclined to agree that men are often “pushed” into roles they don’t really benefit from, and that a jolly good smashing of the patriarchy would be good for them, too. Damore’s reasoning is meandering and inconsistent, however: he is simultaneously protesting that these high-status jobs should be taken from men by women, and complaining that men are the real victims because they are “pushed” into these stressful and dangerous jobs. The first part of his argument is, once again, the old-fashioned idea that men are specially adapted for competition, risk-taking and leadership, while women are not suited to leadership roles and will become unwell if they attempt them. The second part of his argument looks like sheer distraction and a familiar Men’s Rights Activism strategy: trying to convince everyone that men actually have it harder than women.]

Here I omit a portion of the memo, as it doesn’t pertain to the “science” of the matter. But towards the end of the document, in the ‘Suggestions’ section, Damore recommends that Google

Be open about the science of human nature.

Once we acknowledge that not all differences are socially constructed or due to discrimination, we open our eyes to a more accurate view of the human condition which is necessary if we actually want to solve problems.[Again, he makes it sound as though his theory of innate sex differences is a radical new criticism, rather than a dominant ideology that goes all the way back to Aristotle. He also makes it sounds as though science only offers one possible picture of human nature, which is not the case. There is no scientific consensus on human nature, not even on sex differences. The real problem with Damore’s memo, in fact, is that it just isn’t scientific enough.]

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This story only hit my screen yesterday, but on Friday Google employees began tweeting about a document circulating within the company that termed Google’s efforts to increase diversity “discriminatory practices” and calling upon the company to “stop alienating conservatives” and “stop restricting programs and classes to certain genders or races” (that is, to stop running programmes aimed at increasing opportunities for and representation of women and people of colour).1 According to this Google engineer, the real reason that women are underrepresented in “tech and leadership” is not bias but biology. It would seem that the author, now named as James Damore, has since been fired; a controversy rages (anti-sexism and anti-racism vs. “freedom of speech”, roughly), but if you haven’t read all about it already you can look that up for yourself (and you can read the almost-full text of the memo here, obtained by Motherboard and made available by Gizmodo); I’m going to focus on the “biology” bit.

Below is an extract:

Possible non-bias causes of the gender gap in tech [3]

At Google, we’re regularly told that implicit (unconscious) and explicit biases are holding women back in tech and leadership. Of course, men and women experience bias, tech, and the workplace differently and we should be cognizant of this, but it’s far from the whole story.

On average, men and women biologically differ in many ways. These differences aren’t just socially constructed because:

They’re universal across human cultures

They often have clear biological causes and links to prenatal testosterone

Biological males that were castrated at birth and raised as females often still identify and act like males

The underlying traits are highly heritable

They’re exactly what we would predict from an evolutionary psychology perspective

Note, I’m not saying that all men differ from women in the following ways or that these differences are “just.” I’m simply stating that the distribution of preferences and abilities of men and women differ in part due to biological causes and that these differences may explain why we don’t see equal representation of women in tech and leadership. Many of these differences are small and there’s significant overlap between men and women, so you can’t say anything about an individual given these population level distributions.

Personality differences

Women, on average, have more:

Openness directed towards feelings and aesthetics rather than ideas. Women generally also have a stronger interest in people rather than things, relative to men (also interpreted as empathizing vs. systemizing).

These two differences in part explain why women relatively prefer jobs in social or artistic areas. More men may like coding because it requires systemizing and even within SWEs, comparatively more women work on front end, which deals with both people and aesthetics.

Extraversion expressed as gregariousness rather than assertiveness. Also, higher agreeableness.

This leads to women generally having a harder time negotiating salary, asking for raises, speaking up, and leading. Note that these are just average differences and there’s overlap between men and women, but this is seen solely as a women’s issue. This leads to exclusory programs like Stretch and swaths of men without support.

Neuroticism (higher anxiety, lower stress tolerance).This may contribute to the higher levels of anxiety women report on Googlegeist and to the lower number of women in high stress jobs.

Note that contrary to what a social constructionist would argue, research suggests that “greater nation-level gender equality leads to psychological dissimilarity in men’s and women’s personality traits.” Because as “society becomes more prosperous and more egalitarian, innate dispositional differences between men and women have more space to develop and the gap that exists between men and women in their personality becomes wider.” We need to stop assuming that gender gaps imply sexism.

Men’s higher drive for status

We always ask why we don’t see women in top leadership positions, but we never ask why we see so many men in these jobs. These positions often require long, stressful hours that may not be worth it if you want a balanced and fulfilling life.

Status is the primary metric that men are judged on[4], pushing many men into these higher paying, less satisfying jobs for the status that they entail. Note, the same forces that lead men into high pay/high stress jobs in tech and leadership cause men to take undesirable and dangerous jobs like coal mining, garbage collection, and firefighting, and suffer 93% of work-related deaths.2

… Towards the end of the document, in the ‘Suggestions’ section, Damore recommends:

Be open about the science of human nature.

Once we acknowledge that not all differences are socially constructed or due to discrimination, we open our eyes to a more accurate view of the human condition which is necessary if we actually want to solve problems.3

And that’s the extent of his “science.” I’m going to post this while I knock together my critique; it would be great if anyone were to offer their own in the meantime…